Master of Science in Computational Linguistics

The computational linguistics master's program at Rochester trains students to be conversant both in language analysis and computational techniques applied to natural language. The curriculum consists of courses in linguistics and computer science for a total of 32 credit hours.

Graduates from the computational linguistics program will be prepared for both further training at the PhD level in computer science and linguistics, as well as industry positions. A number companies such as Google, Amazon, Nuance, LexisNexis, and Oracle are searching for employees with advanced degrees in computational linguistics for positions ranging from speech recognition technology to improving translation systems to developing better models of language understanding.

Coursework

The curriculum consists of courses in linguistics and computer science, in roughly a 50/50 mix, for a total of 32 credit hours. Four courses (16 credits) are required in linguistics and four courses (16 credits) in computer science. The degree also requires a culminating special written project on a topic relevant to the student's interest and in consultation with individual advisors.

This program’s coursework can typically be completed in three full-time semesters. A fourth semester is for students to prepare their program’s final assignment, project, or thesis.

Linguistics Courses

Prerequisite

Students are required to have completed LING 110 Intro to Linguistic Analysis or its equivalent.

Track Courses

Within linguistics, students will work with an advisor to create a “track” for their coursework in one of three areas:

  • Sound (LING 410, 427, 437, 527, 529, 537)
  • Syntax (LING 420, 460, 461, 462, 520, 560)
  • Semantics (LING 425, 465, 466, 467, 468)

Students will be encouraged to take LING 450 Data Science for Linguistics and LING 501 Research Methods in Linguistics as it suits their programs.

Required

At least one of:

LING 410 Intro to Language Sound Systems
LING 420 Intro to Syntax
LING 425 Intro to Semantic Analysis

At least two of:

LING 427 Phonetics
LING 450 Data Science for Linguistics
LING 460 Syntactic Theory I
LING 461 Constraint Based Syntax
LING 465 Formal Semantics
LING 466 Intro to Pragmatics
LING 468 Computational Semantics
LING 482 Deep Learning Methods in Computational Linguistics
LING 501 Research Methods in Linguistics
LING 520 Syntactic Theory II
LING 527 Prosody

Computer Science Courses

Prerequisites

Students are required to have completed the following prerequisite courses, or its equivalents: 

  • CSC 171 The Science of Programming
  • CSC 172 The Science of Data Structures
  • CSC 173 Computation and Formal Systems
  • MATH 150 Discrete Math
  • MATH 165 Linear Algebra with Differential Equations 
Required

Two of:

LING 424 Intro to Computational Linguistics
CSC 447 Natural Language Processing
CSC 448 Statistical Speech and Language Processing
LING 482 Deep Learning Methods in Computational Linguistics

At least two of:

CSC 440 Data Mining
CSC 442 Artificial Intelligence
CSC 444 Logical Foundation of Artificial Intelligence
CSC 446 Machine Learning

Program Faculty

Linguistics:

Computer Science: